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Super‐resolution for multislice diffusion tensor imaging
Author(s) -
Poot Dirk H. J.,
Jeurissen Ben,
Bastiaensen Yannick,
Veraart Jelle,
Van Hecke Wim,
Parizel Paul M.,
Sijbers Jan
Publication year - 2013
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.24233
Subject(s) - diffusion mri , multislice , image resolution , tractography , voxel , artificial intelligence , computer science , anisotropic diffusion , computer vision , fractional anisotropy , robustness (evolution) , image quality , nuclear magnetic resonance , magnetic resonance imaging , physics , image (mathematics) , chemistry , radiology , medicine , biochemistry , gene
Abstract Diffusion weighted magnetic resonance images are often acquired with single shot multislice imaging sequences, because of their short scanning times and robustness to motion. To minimize noise and acquisition time, images are generally acquired with either anisotropic or isotropic low resolution voxels, which impedes subsequent posterior image processing and visualization. In this article, we propose a super‐resolution method for diffusion weighted imaging that combines anisotropic multislice images to enhance the spatial resolution of diffusion tensor data. Each diffusion weighted image is reconstructed from a set of arbitrarily oriented images with a low through‐plane resolution. The quality of the reconstructed diffusion weighted images was evaluated by diffusion tensor metrics and tractography. Experiments with simulated data, a hardware DTI phantom, as well as in vivo human brain data were conducted. Our results show a significant increase in spatial resolution of the diffusion tensor data while preserving high signal to noise ratio. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.